多化合物和多目标分析可缩放网络的可视化

Data and Text Mining in Bioinformatics Pub Date : 2014-11-07 DOI:10.1145/2665970.2665988

Jaesub Park, Jaeho Kim, Junseok Park, Sunghwa Bae, Hyungseok Kim, Doheon Lee

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引用次数: 0

摘要

近年来，生物数据的爆炸式增长使我们能够在整个身体范围内模拟新陈代谢，这就需要生物信息学工具来对新陈代谢进行可视化和分析。对于这些工具来说，缩放是在单一视图中可视化大型复杂网络的关键方法[1]。但不幸的是，大多数已开发的工具过于依赖于精心构建的层次结构，无法获得缩放功能。为此，我们开发了可缩放的大型生物分子网络可视化系统。

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Visualization of Zoomable Network for Multi-Compounds and Multi-Targets Analysis

Recent explosively increased bio-data enable to simulate the metabolism on whole body scale and it bring about needs of bioinformatics tools for visualizing and analyzing it. For such tools zooming is a key method for visualizing large and complex network in a single view[1]. But unfortunately most of developed tools are too dependent on the elaborately constructed hierarchy to get zoom function. So we developed the zoomable visualization system for the large bio-molecule network without preformed hierarchy data.

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Data and Text Mining in Bioinformatics

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